The network-induced delays (plant-to-controller delay, controller-to-plant delay, and time-delay of plant model), either constant or time-varying, can degrade the performance of control systems designed. Some trends are considered a distributed control over networks which has primarily focused on the development of protocols for networked control system (NCS) with data packet dropout, and limited bandwidth problems. Secondly, the design and analysis of network controllers have paid attention to study for stabilization and performance achievement. This dissertation studies following the second trend. This dissertation investigates area of the modeling, analysis and design of NCS under the effect of randomly varying time-delay and disturbances, which are great interest due to the challengers presented.In particular, the proposed time-delay estimation schemes is designed to server a class of NCS with the presence of network induced delays, data packet dropout and unknown time-delay controlled plant based on Fuzzy logic and Neural network. A Smith predictor mathematical model combined with fuzzy adaptive controller has been designed to adjust on-line its parameters according to the changing of the system's output.Then, we dealt with the stabilization problem of network induced delays, and randomly varying time-delay (RVTD) controlled plant under the effect of the disturbance and noise in NCS. We introduced a novel method to efficiently reducing the effect of the disturbance, noise and time-delays for NCS. This so-called new adaptive Smith predictor NCS composed by two closed loop, the inner loop with disturbance observer is used to eliminate the disturbance and the outer loop is utilized to compensate time-delay of system. The intelligent identification and estimation methods are composing in proposed model which has not only the features of simple Smith predict structure, but also the characteristics of adaptively, stability, and fast response.Finally, we concerned with the robust control problem of the NCS under effect of both network induced delay, RVTD controlled plant, and disturbance. The necessary and sufficient conditions for the robust stability and performance of NCS with adaptive Smith predictor model and disturbance observer based on neural network (NDOB) are given in general formulation. By using the Hoo loop shaping-Mc Farlane and Glover controller design method based on coprime factor robustness and Linear Matrix Inequality (LMI), a novel robust controller has been suggested. The proposed NCS model in our works is a kind of highly efficient which is more feasible and convenient for the application in engineering. |